Building an Adaptive E-Learning System

Christos Chrysoulas, Maria Fasli

Abstract

Research in adaptive learning is mainly focused on improving learners’ learning achievements based mainly on personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed based upon two main sources of personalization information that is, learning behaviour and personal learning style. To determine the initial learning styles of the learner, an initial assigned test is employed in our approach. In order to more precisely reflect the learning behaviours of each learner, the interactions and learning results of each learner are thoroughly recorded and in depth analysed, based on advanced machine learning techniques, when adjusting the subject materials. Based on this rather innovative approach, an adaptive learning prototype system has been developed.

References

  1. Agrawal, R., Srikant, R. (1994). Fast algorithms for mining association rules, in: Proc. 20th Int. Conf. Very Large Data Bases, VLDB, 1994, pp. 487- 499.
  2. Brookfield, S. (2009). Self-directed learning. In R. Maclean & D. N. Wilson (Eds.), International handbook of education for the changing world of work (pp. 2615-2627). Dordrecht: Springer. http://dx.doi.org/10.1007/978-1-4020-5281-1.
  3. Fuseki: serving RDF data over HTTP. (2016) https://jena.apache.org/documentation/serving_data/ Hwang, G. J. (2002). On the development of a cooperative tutoring environment on computer networks. IEEE Transactions on System, Man and Cybernetic Part C, 32(3), 272-278.
  4. Kamceva, E., Mitrevski, P. (2012). On the General Paradigms for Implementing Adaptive e- Learning Systems”, ICT Innovation Web Proceedings ISSN 1857-7288, pp.281-289.
  5. OAuth 2.0: The OAuth 2.0 Authorization Framework (2012). https://tools.ietf.org/html/rfc6749.
  6. Pinto, J., Ng, P., Williams, S. K. (2008). The Effects of Learning Styles on Course Performance: A Quantile Regression Analysis. Franke College of Business, Working Paper Series - 08-02.
  7. Santally, M. I., Alain, S. (2006). Personalisation in Webbased learning environments. International Journal of Distance Education Technologies, 4(4), 15-35.
  8. Slimani, T. (2013). Description and Evaluation of Semantic Similarity Measures Approaches. International Journal of Computer Applications 80(10):25-33.
  9. Triantafillou, E., Pomportsis, A., Demetriadis, S., Georgiadou, E. (2004). The value of adaptivity based on cognitive style: an empirical study. British Journal of Educational Technology, 35(1), 95-106.
  10. Tsai, C.-C. (2004). Beyond cognitive and metacognitive tools: The use of the Internet as an "epistemological" tool for instruction. British Journal of Educational Technology, 35, 525-536.
  11. Villaverde, J.E., Godoy, D., Amandi, A. (2006). “Learning styles” recognition in e-learning environments with feed-forward neural networks. Journal compilation and Blackwell Publishing Ltd, pp. 197-206.
  12. W3C Resource Description Framework Working Group (2014). https://www.w3.org/ standards/techs /rdf#w3c_all.
  13. W3C SPARQL Query Language for RDF (2013). https://www.w3.org/TR/rdf-sparql-query/
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Paper Citation


in Harvard Style

Chrysoulas C. and Fasli M. (2017). Building an Adaptive E-Learning System . In Proceedings of the 9th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-240-0, pages 375-382. DOI: 10.5220/0006326103750382


in Bibtex Style

@conference{csedu17,
author={Christos Chrysoulas and Maria Fasli},
title={Building an Adaptive E-Learning System},
booktitle={Proceedings of the 9th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2017},
pages={375-382},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006326103750382},
isbn={978-989-758-240-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - Building an Adaptive E-Learning System
SN - 978-989-758-240-0
AU - Chrysoulas C.
AU - Fasli M.
PY - 2017
SP - 375
EP - 382
DO - 10.5220/0006326103750382